AI Weekly Malaysia

1337 Ventures has published its 2026 Request for Startups, listing seven problem areas it wants to back at pre-seed: Vertical AI & Agentic Workflows; Fintech, Trust & Compliance; Industrial AI & Smart Manufacturing; HealthTech & Care Infrastructure; Food, Agriculture & Supply Chains; Climate Intelligence & Resource Efficiency; and Semiconductor & HardTech Enablement. The firm says it is targeting companies where roughly US$37,000–US$122,000 (RM150,000–RM500,000) of early capital is enough to build an MVP, land first design partners, run pilots, or generate evidence for a seed round. Founding partner and CEO Bikesh Lakhmichand frames the themes around a specific test for founders: what you understand about an industry deeply enough that a general AI platform cannot easily replace you, since AI is now a horizontal layer rather than its own vertical.

Why: If you are building in Malaysia and deciding what to pitch or how to scope a first product, this is a concrete filter rather than a sector list: seven named themes plus a stated cheque band of RM150,000–RM500,000, which is MVP-and-first-pilots money, not fab or solar-farm money. The RFS explicitly ties themes to Penang's semiconductor ecosystem, Johor's cross-border integration with Singapore, Sarawak's energy and digital infrastructure, and national industrial automation policy, so a founder can check whether their wedge sits on one of those structural shifts before spending months on a deck. It also sets an expectation that applicants should answer the 'why can't a frontier model do this' question in the pitch.

Exabytes founder and CEO Chan Kee Siak argues Malaysian SMEs get little from agentic AI unless they re-engineer existing workflows and have bosses who personally use AI, recommending phased adoption starting with standalone agents. He cites an Ecosystm and Red Hat study of 133 Malaysian SMEs, supported by the National AI Office, showing only 21% moved past AI pilots and about 60% cited a lack of in-house technical expertise. Exabytes itself is putting more than 50% of its budget into AI, targeting one million businesses adopting AI by 2030, opened an HPC/AI colocation facility in Penang, signed an MoU with Aurora Mobile, and now draws roughly 30% of revenue from AI and cloud.

Why: If you sell or build for Malaysian SMEs, the survey number that matters is the 60% citing no in-house technical expertise and the 79% stuck in pilots, not the model access problem — the paid work is workflow redesign plus ongoing support, not another chatbot. It also sets a concrete benchmark for local demand: Exabytes claims 160,000 business customers (90% SMEs) and 30% of revenue from AI and cloud, so a small team should decide whether to compete on agent delivery or on the unglamorous integration and change-management layer.

Wabi, the prompt-to-app startup founded by Eugenia Kuyda (who previously founded Replika), announced 'Wabi 2.0' on September 28 — an invite-only AI messenger that generates the interface it needs in the moment, rather than competing head-on with other vibe-coding tools. Kuyda's stated rationale is that chat-only agents degrade with use because history and ongoing tasks end up buried in one endless scroll. The pivot lands the same week OpenAI's Dev Day announced updated ChatGPT plugins, which let apps offer interactive experiences inside ChatGPT with the app name pinned more visibly in the sidebar.

Why: If you ship a vibe-coded app or an agent product, this is a fork in the road: build your own messenger-style surface that generates UI on demand, or distribute inside ChatGPT's sidebar via the updated plugins and trade control for reach. The article gives no pricing, launch date beyond 'invite-only', or user numbers for Wabi 2.0, and no technical detail on how the generated interfaces work — so treat it as a positioning signal, not a validated playbook. Nothing here is Malaysia-specific.

Peak XV Partners raised the per-company investment ceiling for its Surge seed platform from $3M to $5M, and Surge 12 — its first cohort under the new cap — has 18 startups, with the firm investing more than $50M across the batch, which collectively raised over $90M in seed funding. Managing director Rajan Anandan said the bar to raise a Series A has gone up significantly and that capital-intensive deeptech companies are raising larger seed rounds. Of the 18 startups, only five target the Indian market, more than half are based in India, and the rest target global markets, with founders spanning San Francisco to Sydney.

Why: For founders raising in Southeast Asia, the reference point for seed size has moved: Surge now writes up to $5M per company versus $3M, and the cohort's $90M+ total seed raise shows larger early rounds are normal. Combined with Anandan's point that the Series A bar has risen, the practical decision is to size your seed round against the milestones a Series A now requires rather than against a previous $3M-era default — and to note that 13 of these 18 companies are built in one market but sell globally, so an India-built, globally-sold company is a live template for regional founders.

Factory CEO Matan Grinberg posted on X on Sept 30 that he fired VC Chris Degnan as a board advisor, alleging Degnan shared confidential information with Cognition, which Grinberg calls Factory's biggest competitor. Two hours later Degnan announced on X and LinkedIn that he had joined Cognition as chief revenue officer, denied the allegations, and said he resigned rather than was fired. Degnan, Snowflake's first sales hire and its CRO for 11 years, had spent the last five months as a partner at Newport Beach-based RPT Partners, an investor in Factory, and also advises startups on go-to-market for Iconiq.

Why: Factory raised $200M at a $5B valuation this month with customers including Nvidia, Adobe and T-Mobile, while Cognition (maker of Devin) raised $2B at a $48B valuation with customers including Goldman Sachs and Citi — so this is a governance fight between two funded agentic-coding rivals, not a product change. If you take board advisors or GTM advisors from funds that also back competitors, this is a concrete case for writing confidentiality and conflict-of-interest terms into advisor agreements and controlling what roadmap and pipeline data such advisors can see. Nothing here changes code you ship or a tool you use today.

ElevenLabs is letting employees sell vested shares in a $300 million tender offer at a $22 billion valuation, double the $11 billion it hit when it raised $500 million in February 2026. The deal was co-led by Wellington and T. Rowe Price, and it's the four-year-old company's second employee secondary — the first was a $100 million tender at a $6.6 billion valuation in September 2025. ElevenLabs, founded in 2022 and described as New York- and London-based, makes voice and sound-effect generation models.

Why: There is no product, pricing, or API change in this story, so nobody's build breaks and no cost changes. The concrete signal is for founders and early employees: this is the second liquidity event in about 12 months, and TechCrunch frames employee tenders as a retention tool against staff leaving for competitors — if you're structuring equity at a small startup, that's the pattern being normalized at the top of the market, not a reason to re-plan your own roadmap.

TechCrunch profiles DetectifAI, a San Francisco-based company founded by Tarini Padmanabhuni after her grandfather paid a ransom to a deepfake voice imitating his brother roughly two years ago. DetectifAI's pitch is that it designs compact models from the start to run inside a phone's operating system, giving an on-device verdict on whether a voice in calls, voice messages, or other audio is AI-generated, rather than shrinking cloud models as competitors do. It is licensing its tools first to phone manufacturers, and cites FBI figures that Americans lost close to $900 million to AI-driven scams last year, up 24% from 2024, with people 60 and older losing twice as much as those aged 50 to 59.

Why: The concrete detail here is the distribution choice: DetectifAI is selling to phone makers as an OS-level licence, not shipping an app you can install, so there is nothing for a builder to try today. If you are thinking about scam/deepfake defence for Malaysian users, the useful question is which layer you can actually reach (banking app, telco, OEM) and whether on-device inference fits your latency and privacy constraints, since audio never leaving the handset is the specific claim being made. Treat the $900M/+24% FBI figure as the size of the scam problem, and note the item gives no benchmarks, pricing, or availability.

Marissa Mayer, described in the article as former Yahoo CEO, unveiled Dazzle, a personal AI assistant that raised an $8 million seed round last December and pulls all of its context from one source: your camera roll, rather than email, calendar, or shopping history. In a TechCrunch demo, Dazzle handled immediate tasks like populating a calendar from an event flyer and finding a repair person after spotting a broken garage door, while also claiming to infer hobbies, recent trips, food and style preferences, and what your kids are into. Mayer's previous startup, Sunshine, shipped an AI photo-sharing tool called Shine in 2024; the article says it was criticized for outdated design, failed to gain widespread usage, and shut down.

Why: The pitch here is a context-source bet, not a model bet: Dazzle deliberately ignores inbox and calendar data that Meta's Muse, Instinct, and the wave of assistants launched in the past month lean on. If you build consumer agents, the concrete question this raises is which single data source gives the best context per unit of privacy risk and integration work — and the article gives no pricing, launch date, or technical detail, so there is nothing here to change in your stack yet. The $8M seed also signals that a demo-plus-photo-roll thesis is still fundable in a month where several competitors shipped.

Lenny Rachitsky published the full main-stage playlist from the Lenny & Friends Summit (posted Sep 29, 2026), including talks from Katie Dill (Stripe), Dan Shipper (Every), Geoff Charles (Ramp), Tamar Yehoshua (Atlassian), Robby Stein (Google Search), Elena Verna (Lovable), Marty Cagan (SVPG), Karri Saarinen (Linear), plus panels with Anthropic's Ami Vora and Mike Krieger and OpenAI's Tara Seshan and Nan Yu. The post lists talk titles only — no slides, transcripts, or technical detail — and adds Rachitsky's five reflections, led by his claim of unusually strong demand for curated in-person events and the observation that working with agents makes the job lonelier. He notes speakers took opposing sides on whether roadmaps are over, whether teams should build 'software factories', and whether PMs should ship to production.

Why: This is a free, named video library rather than an announcement you must react to — the concrete decision is which single talk to watch this week. If your team is arguing about AI-era process, three of the listed talks map directly onto that argument: Geoff Charles (Ramp) on designing an 'AI software factory' for speed, Claire Vo's 'The last roadmap', and Karri Saarinen (Linear) on 'context is now the product'. The organizer's claim of exceptional demand for curated IRL events is the only data point here that touches Malaysian builders: it is an argument that local meetups still fill rooms even as agent tooling spreads.

TechCrunch reports, citing a source with knowledge of the deal, that AI inference provider Modal Labs is close to a $750 million round led by Accel at a $15.75 billion valuation — more than triple the $4.65 billion it hit in its $355 million raise just four months earlier. The article notes the wider inference market is repricing fast: Baseten is reportedly nearing a round at a $26 billion valuation (double its June number), Fireworks said in July its annualized revenue hit $1 billion (5x year over year), and Fal has also talked to investors. It also flags the catch: revenue is growing quickly but margins are thin because acquiring or leasing compute stays expensive.

Why: This is a capital-markets signal, not a product change — no pricing, API, or capability change is stated, so there is nothing to migrate or re-architect today. The one decision-relevant detail is the thin-margin caveat alongside Fireworks' $1B annualized revenue: if you are choosing an inference provider for a production or agent workload, expect competition to keep going up while compute costs keep the providers' margins thin, which makes multi-provider abstraction and exit cost worth designing for before you commit. Nothing here is Malaysia-specific; treat it as context on the vendors a Malaysian team might depend on, not as local market news.

TechCrunch rounds up AI agents that operate inside text messaging rather than a standalone app, including Caddy (iMessage on iPhone, RCS on Android, in public beta since April 2026, connects to calendars and conversations to add events, set reminders, track follow-ups, and run research), Fambot (a family 'chief of staff' spanning school comms, sports, meal planning, and calendars across iOS, Android, web, and text), and Instinct, cited as one of the buzziest agents after a $1B funding round at a $10B valuation. The piece is a directory of options rather than an evaluation, and the excerpt cuts off mid-entry on Fambot.

Why: The concrete decision here is surface area: Caddy lives in iMessage for iPhone and RCS for Android, so an agent distributed over texting skips app-store install friction but inherits the host platform's rules and RCS availability, which the article does not specify per market. If you are weighing a messaging-first agent for Malaysian users, treat 'no app to download' as a distribution hypothesis to validate on both iOS and Android devices your users actually carry, not as a solved channel. Note the roundup gives no pricing, no reliability data, and no independent testing, so it is a starting list to try, not evidence any of these agents work well.

Kevin Mandia — founder of Mandiant, which sold to Google for $5.4B in 2022 — raised $255.5M for a new security startup, Armadin, at a valuation above $2.5B. The Series B was led by Andreessen Horowitz and Accel, with Bain Capital Ventures, Redpoint, 8VC, Ballistic Ventures, Google Ventures, In-Q-Tel, Kleiner Perkins, and Menlo Ventures participating, and it comes just six months after a $190M Series A in March, bringing total funding past $445M. Armadin's pitch is replacing periodic human penetration tests with always-on agentic swarms that chain vulnerabilities together to hack in, so enterprises find and seal holes before attackers or 'rogue' AI agents do.

Why: This is a funding announcement with no product pricing, named customers, or benchmark data in the text, so it is not a buying signal — but it is a directional one: a16z, Accel, GV, and In-Q-Tel just put $445M+ behind agentic offensive security in under a year, which means 'always-on agent swarm pentesting' is now a funded category rather than a demo. If you run periodic pentests for a SaaS product or you're building agent tooling, expect vendors to pitch swarm-based continuous testing against your existing pentest cadence, and expect to have to ask for evidence — detection rates, false-positive rates, blast radius controls — that this announcement does not provide.

On an interview with investor Patrick O'Shaughnessy, Instinct founder Noah Shinn said more than 50% of transactions on the invite-only agent platform are travel-related, and that the platform is approaching a billion dollars in annual transactions while growing "10% day-by-day" with transaction volume rising at a similar rate. Shinn did not specify how the transaction rate is calculated. He also described agents checking restaurant sites every five seconds for open slots and said he wants to "reinvent reservations" to give users preferential treatment, comments that drew criticism.

Why: Treat the numbers as self-reported with no stated methodology: a 10% day-over-day growth rate and ~$1B annual transaction figure would be extraordinary at that compounding rate, so don't use them for capacity planning, market sizing, or a pitch deck without your own verification. The one reusable technical detail is the pattern of an agent polling a third-party restaurant site every five seconds for availability — if you build anything similar, expect rate limits, bot blocking, and server-cost questions from the sites you scrape, and design caching or webhook/API fallbacks rather than tight polling loops.

Boston-based Atomic raised a $12.5M Series A led by Klass Capital and Madrona Venture Group, bringing total funding to just over $15M. Atomic simulates supply-chain scenarios and then recommends or automatically picks inventory levels and locations, and its ARR has quintupled since the start of 2026, with named customers DoorDash and HelloFresh. The company was incubated at DVx Ventures, has added longtime Tesla planning director Jeff Goodrich as CTO and third co-founder, and traces its system back to an early version built during Tesla's 2018 Model 3 production ramp.

Why: This is a funding announcement, not a product you can adopt: no pricing, no self-serve tier, no technical benchmarks, and the customers named are US enterprise brands. Treat it as a category signal that 'AI picks the inventory decision, not just forecasts it' is attracting capital, and note CEO Michael Rossiter's own framing is simulation plus path-finding over an infinite decision space — not a claim of measured accuracy. If you build logistics or ops tooling for Southeast Asian merchants, the useful takeaway is that the funded wedge is auto-execution on top of existing planning data, which is a harder trust problem than forecasting.

Mavi, founded in 2023 by co-CEOs Molly Liu and Aman Puri, emerged from stealth on Monday Sept 28, 2026 as an AI-powered talent marketplace that places mid- and senior-level global finance and accounting staff with U.S. companies "within days," and also handles cross-border contracts, legal, compliance, and payroll. Liu, whose prior work the article places at Ramp, Lyft, and Dropbox, argues AI will automate away many entry-level finance roles, shrinking the pipeline of people who grow into mid-level positions. No funding amount, pricing, fee model, or named customers are disclosed in the text.

Why: The concrete claim to test is 'placement in days' bundled with cross-border contracts, compliance, and payroll — that is an employer-of-record-style middle layer, not just a job board. If you hire finance or ops staff, the decision is whether that bundle beats hiring directly or using an established EOR, and the article gives you no pricing or customer references to compare with, so treat the pitch as unverified. The transferable point for builders: Liu's thesis is that automating entry-level work removes the training ground for mid-level roles, which is the same argument now aimed at junior developer and analyst hiring.

Modulate, a Boston-based voice intelligence startup founded in 2017 by Mike Pappas and Carter Huffman, raised $25M led by Future Ventures with Hyperplane and Lakestar participating, after previously raising $41M at a $170M valuation per PitchBook. The platform runs more than 100 small models split into two groups: signal extraction (vocal emotion, tone, language, synthetic-voice detection) and analysis/detection (caller intent and policy enforcement for voice agents in regulated industries). The announcement carries no pricing, API, benchmark, or availability details.

Why: This is a funding announcement, not a product you can adopt this week — there is no pricing, endpoint, or accuracy number in the text, so there is nothing to integrate or benchmark. The one decision-relevant signal is architectural: Modulate is betting on 100+ small specialised models rather than one large multimodal model for emotion, intent and deepfake detection in live calls, which is the opposite of the default 'one big LLM' approach most teams reach for. If you are building voice agents for regulated verticals, treat 'intent classification plus policy enforcement on the call' as a component you will likely have to either buy or build, and note that no Malaysian or SEA pricing, data-residency, or language-coverage detail is given here.

Singapore-based ride-hailing firm Ryde, listed on the NYSE, is facing a shareholder petition and a US class action. Octava Fund filed a Cayman Islands petition on Jul 3 seeking a buyout of Ryde's 6.9 million shares or a wind-up over alleged improper governance and breach of duty, while a Sept 10 class action in the Southern District of New York alleges a pump-and-dump scheme. Ryde said on Sept 18 that the proceedings are at an early stage, no findings have been made, no liquidator has been appointed, directors remain in control, and it intends to defend the class action.

Why: For SEA founders, this is a concrete post-listing governance risk: a Cayman-incorporated, Singapore-operating company can face a shareholder petition over 6.9 million shares and a US class action alleging pump-and-dump. It does not change any developer tooling, so most Malaysian builders can treat it as a startup/funding cautionary note rather than an action item.

Flow Engineering, a three-year-old San Francisco startup making AI agents that align CAD drawings with product requirements, simulation results, and other test data, raised a $50M Series B at a $750M valuation, announced September 30, 2026. The round was co-led by Antonio Gracias of Valar Equity Partners and Gavin Baker of Atreides Management, with Sequoia Capital (which led the Series A last October) participating and former Sequoia partner Roelof Botha investing individually and joining the board. Named customers are Anduril, Rivian, Joby Aviation, General Motors PPU, RV Tech (a Rivian–Volkswagen joint venture), and Stoke Space.

Why: There is no product release, pricing, API, or benchmark in this piece, so no builder has anything to change because of it — it is a funding announcement with a customer logo list. The one concrete read for a founder is market signal, not tooling: agentic verification of CAD/simulation artifacts is being priced at a $750M valuation with reference customers in defense, EV, aerospace, and motorsport (Anduril, Rivian, Joby, Stoke Space), which suggests regulated, high-cost physical-engineering workflows are where agents command enterprise budgets. Nothing in the text connects this to Malaysia or Southeast Asia, so treat any local angle as unverified.

Aurora CFO David Maday told TechCrunch that the company's target of 30,000 driverless trucks and $5 billion in annual revenue by end of 2030 is achievable, arguing 30,000 is small against the 250,000-300,000 new trucks the four major manufacturers build each year. Aurora expects to finish 2026 with just 200 driverless trucks and an $80 million revenue run rate, moving to 1,000+ trucks in 2027 and shifting from its current ~$2-per-mile transportation-as-a-service model (capped at ~500 trucks, with customers including Werner, McLane, Hirschbach and Detmar Logistics) to a driver-as-a-service model. Investors are unconvinced: shares closed down 12.42% to $5.29 on Monday, continuing to slide since the September 23 analyst day.

Why: This is a company's own forward projection, not an independent measurement, so treat the 30,000-truck figure as a sales narrative rather than a forecast you can plan around. The only hard signals in the text are the current numbers: 200 trucks and an $80M run rate at end-2026, a 1,000-truck 2027 step, and a 12.42% single-day share drop after the analyst day. If you are building anything on autonomous freight capacity assumptions, the 2027 transition to driver-as-a-service is the concrete date to watch, not 2030.

MyMonthlyCar, co-founded by Igor Dobrianskyi with Kostiantyn Gitko as chief product officer and Vadym Zotov as CTO, is building a platform that rents used cars from dealerships on a month-to-month basis, with an optional rent-to-own path. The company cites 76,000 US dealerships sitting on depreciating inventory and charges dealers 10% of each transaction plus a separate 10% fee to the customer, with no listing fee. It is registered in Delaware, based in Florida, and was selected for the 2026 Startup Battlefield 200, exhibiting at TechCrunch Disrupt on October 13–15 in San Francisco.

Why: This is a startup profile, not a product launch you can use, and nothing in the text touches Malaysia or Southeast Asia, so there is no local decision to make from it. The one transferable number for marketplace builders is the 20% combined take rate (10% dealer + 10% renter) on a depreciating physical asset, which is high for a two-sided rental marketplace and worth stress-testing against dealer margins if you are modeling anything similar.

Y Combinator announced on October 1, 2026 that Vivian Midha Shen and Raphael Schaad are joining as General Partners, after both spent the last two batches as Visiting Partners. Vivian co-founded Juni Learning (YC W18) and Acely, an AI college-readiness tutor that the post says went from zero to $10 million run rate with a lean team, with over $50 million in combined revenue across both companies. Raphael founded Cron (YC W20), which Notion acquired in 2022, then grew Notion Calendar to millions of users and served as Head of Design for Growth and new products; he previously worked on Flipboard and iA Writer.

Why: This is a personnel announcement from YC's own blog with no product, pricing, policy, or program change attached, so there is nothing concrete to act on this week. The only usable signal for founders weighing a YC application is who reads it: both new GPs come from small, craft-heavy, AI-native consumer products (Acely's cited 0-to-$10M run rate with a lean team; Cron's design-led acquisition by Notion), not from growth or sales backgrounds. Treat that as context, not a change to any stated selection criteria.

TechCrunch's Equity podcast episode features Farooq Abbasi, founder and general partner of Preface Ventures and an investor in Neko Health, discussing the company's $700 million raise to build a preventative body-scanning business. The episode covers what Neko's $500 scan actually includes, how the company keeps that price down, why Abbasi sees low primary-care utilization as one of the biggest problems in U.S. healthcare, and his view that some consumer-health startups may be overfunded. The show also notes Midjourney is building its own body scanner and that Function Health has raised significant capital for a preventative-health platform.

Why: This is a podcast promo, not new product or pricing news, so nothing here changes what you build this week. The one reusable number is the $500 scan price and the claim that Neko keeps it down through its own operations — if you are modelling consumer health or diagnostics pricing for a Malaysian or SEA market, that unit-economics question (what a scan must cost to be repeatable without insurance) is the part worth stealing, and the episode reportedly discusses it. Otherwise treat the $700M figure as a funding headline, not a signal about your roadmap.

BAG Ventures, founded by former Google VP Bonita Stewart and former CapitalG partner Jackson Georges Jr., closed an $11.3M fund for early-stage AI startups after roughly two years of investing out of it. It has already backed 10 companies — including SXD, AI travel agent BizTrip, and agentic reasoning platform Nomadic — with check sizes of $100,000 to $500,000, and plans to deploy the rest over the next two years across AI infrastructure, compute, physical/edge AI, security, governance, and vertical SaaS. The pair describe their edge as access: warm introductions to enterprise operators rather than capital alone.

Why: If you are raising in the $100K–$500K band for an enterprise-facing AI product, this is one more pre-seed/seed option, and the pitch is explicitly about operator introductions into buyer organisations, not just money — so the useful question is whether that network maps to your target accounts. Nothing in the text ties the fund to Malaysia or Southeast Asia, so there is no stated local angle here; treat it as background on where early AI money is going, not as an opportunity you must act on.

Cloudflare announced 'The Cold Start', a live startup competition at Cloudflare Connect in San Francisco this October, where five early-stage companies each get five minutes on stage to explain what they're building and why it needs to exist. The post is framed around Cloudflare's own 2010 TechCrunch Disrupt Startup Battlefield launch by Matthew Prince and Michelle Zatlyn, which drew hundreds of signups during the Q&A and saw network traffic rise nearly 10x in the following seven days. The excerpt cuts off before stating any prize, funding, equity terms, or application deadline.

Why: Only useful if you're an early-stage founder who can physically be in San Francisco in October — the post gives no prize, investment, equity, or deadline details (the text is truncated mid-sentence), so there is nothing here to act on for a Malaysia-based builder beyond noting that this kind of stage is geographically gated. The one transferable detail is the stated selection bar: five minutes, vision over deck polish, no TAM slide required — which is a reasonable template for how to pitch anywhere, including local demo days.

TechCrunch rode Vessev's VS-9 electric ferry from Brooklyn Marina toward Governors Island. The roughly 30-foot hydrofoil catamaran uses two underwater foils with computer-controlled flaps; the front foil handles about 80% of lift and the rear about 20%, and the rear foil houses Vessev's in-house electric motor. The batteries are outsourced because Vessev's CEO calls them commoditized, and the foils can be raised for shallow docks.

Why: This is a transportation/hardware product ride report with no pricing, range, charging, certification, deployment date, or Malaysia/SEA angle in the text, so most developers and SaaS founders have no action to take. Hardware founders may note Vessev's make-vs-buy split: build the electric motor in-house for cost control while treating batteries as a commodity.